Visibility-Based Motion Planning

在许多环境中，产生了为具有基于可见性的感测能力的真实的和虚拟机器人系统生成运动策略的问题。最后一个术语是指传感器的能力（例如，摄像机或距离传感器）来检测沿着沿着一条或几条穿过自由空间的视线的物体。 一个新的概念框架和特定的新算法的集合，需要执行运动规划下的可见性约束，除了经典的避碰约束处理以前的规划。 这些算法的输出将是运动策略， 运动 命令 与 基于可视 传感操作。 虽然机器人技术已经广泛地研究了在完全已知的环境中操作的机器人的运动规划问题，几乎没有或没有感测能力，并且主动视觉已经研究了局部相机运动/控制的问题，以获取所需的数据，但是可见度感测与运动规划的集成仍然相对未被探索。然而，机器人的各种重要任务都可以用可见性的语言来表达。 “计划一次游览，以便看到所有感兴趣的区域”，“移动到所需的位置，同时保持对目标的视线，” “保持一个移动的目标进入视线， “视野阻挡移动的对象”只是这些任务的一些示例。 由于基于能力的传感允许机器人在部分未知的环境中操作，这些技术允许适用于动态环境的在线规划。 制造业 并且医学可以受益于这些方法的应用，特别是在那些手术中（例如，零件交付、装配、监控）的复杂性。

In many environments the problem arises of generating motion strategies for real and virtual robotic systems with visibility- based sensing capabilities. This last term refers to the ability of a sensor (e.g., a video camera or a range sensor) to detect objects along one or several line-of-sight rays through free space. Both a new conceptual framework and a collection of specific new algorithms are needed to perform motion planning under visibility constraints, in addition to the classical collision avoidance constraints dealt with by previous planners. The output of these algorithms will be motion strategies that integrate motion commands with visibility-based sensing operations. While robotics has extensively studied the motion planling problem for robots operating in fully known environments with little or no sensing ability, and active vision has studied the problem of local camera motion/control in order to acquire needed data, the integration of visibility sensing with motion planning has remained relatively unexplored. Yet a variety of important tasks for a robot can be expressed in the language of visibility. `Plan a tour so as to see all of the region of interest,' `move to the desired location while keeping sight of a target,' `keep a moving target into sight despite view- obstructing mobile objects' are just some examples of such tasks. As visibility-based sensing allows robots to operate in partially unknown environments, these techniques allow on-line planning applicable to dynamic environments. Both manufacturing and medicine can benefit from application of such methods, especially in those operations (e.g., part delivery, assembly, monitoring) that occur in heavily occluded and dynamic work environments.